Course Overview
Building Data Lakes on AWS is an intermediate-level course focused on designing and building operational data lakes that support analysis of structured and unstructured data. The course covers the key AWS services and components used to create, secure, catalog, process, query, and visualize data within a data lake. AWS currently lists Building Data Lakes on AWS as an intermediate, one-day classroom course within its Data Analytics training portfolio.
Participants work with AWS Lake Formation to build and secure a data lake, AWS Glue to create a data catalog and process data, Amazon Athena to query and analyze data, and Amazon QuickSight for visualization. The course includes presentations, lectures, hands-on labs, and group exercises covering common data lake architectures.
Course Objective
- Apply data lake methodologies in planning and designing a data lake
- Identify the components and AWS services required to build a data lake
- Secure a data lake with appropriate permissions
- Ingest data into a data lake
- Store data within a data lake
- Transform data within a data lake
- Query data using Amazon Athena
- Analyze data within a data lake
- Visualize data from a data lake using Amazon QuickSight
Pre-requisites
- Completed the AWS Technical Essentials classroom course
- One year of experience building data analytics pipelines, or completion of the Data Analytics Fundamentals digital course
Course Curriculum
